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I am graduating as a fifth year PhD student and I really agree with Professor David Karger from MIT about the qualities characterizing a great PhD student, especially about the point on “discipline and productivity”. Professor Karger also distinguished the difference between a successful PhD for industry and a successful PhD for academic. Here I just cite the whole article to share with you as well as to keep these principles in my own mind:

As a CS prof at MIT, I have had the privilege of working with some of the very best PhD students anywhere.  But even here there are some PhDs that clearly stand out as *great*.   I’m going to give two answers, depending on your interpretation of “great”.

For my first answer I’d select four indispensable qualities:
0. intelligence
1. curiosity
2. creativity
3. discipline and productivity
(interestingly, I’d say the same four qualities characterize great artists).

In the “nice to have but not essential” category, I would add
4. ability to teach/communicate with an audience
5. ability to communicate with peers

The primary purpose of PhD work is to advance human knowledge.  Since you’re working at the edge of what we know, the material you’re working with is hard—you have to be smart enough to master it (intelligence).  This is what qualifying exams are about.   But you only need to be smart *enough*—I’ve met a few spectacularly brilliant PhD students, and plenty of others who were just smart enough.  This didn’t really make a difference in the quality of their PhDs (though it does effect their choice of area—more of the truly brilliant go into the theoretical areas).

But intelligence is just a starting point.  The first thing you actually have to *do* to advance human knowledge is ask questions about why things are the way they are and how they could be made better (curiosity).  PhD students spend lots of time asking questions to which they don’t know the answer, so you’d better really enjoy this.  Obviously, after you ask the questions you have to come up with the answers.  And you have to be able to think in new directions to answer those questions (creativity).  For if you can answer those questions using tried and true techniques, then they really aren’t research questions—they’re just things we already know for which we just haven’t gotten around to filling in the detail.

These two qualities are critical for a great PhD, but also lead to one of the most common failure modes: students who love asking questions and thinking about cool ways to answer them, but never actually *do* the work necessary to try out the answer.  Instead, they flutter off to the next cool idea.  So this is where discipline comes in: you need to be willing to bang your head against the wall for months (theoretician) or spend months hacking code (practitioner), in order to flesh out your creative idea and validate it.  You need a long-term view that reminds you why you are doing this even when the fun parts (brainstorming and curiosity-satisfying) aren’t happening.

Communication skills are really valuable but sometimes dispensable.  Your work can have a lot more impact if you are able to spread it to others who can incorporate it in their work.  And many times you can achieve more by collaborating with others who bring different skills and insights to a problem.  On the other hand, some of the greatest work (especially theoretical work) has been done by lone figures locked in their offices who publish obscure hard to read papers; when that work is great enough, it eventually spreads into the community even if the originator isn’t trying to make it do so.

My second answer is more cynical.  If you think about it, someone coming to do a PhD is entering an environment filled with people who excel at items 0-5 in my list.  And most of those items are talents that faculty can continue to exercise as faculty, because really curiosity, creativity, and communication don’t take that much time to do well.  The one place where faculty really need help is on productivity: they’re trying to advance a huge number of projects simultaneously and really don’t have the cycles to carry out the necessary work.   So another way to characterize what makes a great PhD student is

0. intelligence
1. discipline and productivity

If you are off the scale in your productivity (producing code, running interviews, or working at a lab bench) and smart enough to understand the work you get asked to do, then you can be the extra pair of productive hands that the faculty member desperately needs.  Your advisor can generate questions and creative ways to answer them, and you can execute.  After a few years of this, they’ll thank you with a PhD.

If all you want is the PhD, this second approach is a fine one.  But you should recognize that in this case that advisor is *not* going to write a recommendation letter that will get you a faculty position (though they’ll be happy to praise you to Google).  There’s only 1 way to be a successful *faculty member*, and that’s my first answer above.

Update: Here is another article from Professors Mark Dredze (Johns Hopkins University) and Hanna M. Wallach (University of Massachusetts Amherst).

I collected the following series on applying for faculty positions in 2011, when I was in my second year PhD. Now it’s my turn to apply for jobs. I will share the following useful materials with all you who want to apply for jobs this year.

  1. Applying for Jobs: Application Materials
  2. Applying for Jobs : Sending out Applications
  3. Applying for Jobs : Phone Interviews
  4. Applying for Jobs: On-Site Interviews
  5. Applying for Jobs: the Job Talk

I just attended GAW18, which was held October 13-17, 2012 at the Skamania Lodge in the beautiful Colombia River Gorge, Stevenson WA. It is a good experience for me and I think I will come back later to talk more about what I have learned from there.

Lana Yarosh shared her with us 5 practices (developed through much trial and error) that helped her stay happy in grad school:

  • Pick a good conference in your field and go to it every year (including your first year, even if you have to pay for it out of pocket) — when there were times that I thought about quitting (and there were those times), a conference has always brought me the energy, the influx of new ideas, and the wonderful people that I needed to get back in gear. My two chosen conferences are CHI (Human Factors in Computing) and IDC (Interaction Design and Children).
  • Avoid “time shifting” whenever possible — time shifting is when you end up shifting something you need to do today to another day in order to do some piece of work (e.g., “I’ll sleep tomorrow,” “I’ll get in touch with my advisor some other day, today I need to focus on this paper,” etc.). In my experience, time shifting only makes me more stressed out and less productive in the long run. If you need to skip this conference deadline and try for another, then maybe that’s the thing to do.
  • Get to know the people in your program — these folks are not only great to get to know as friends, but also will likely be your colleagues in the years to come. Also, they can commiserate with anything that you’re currently facing so they’re a great source of social support.
  • Have a routine that includes all of the things that are important to you — make a list of what is important to your happiness and make sure that you get a chance to do these things. My list includes things like swimming, hanging out with friends, exploring new places, reading for fun, and yes, research. You may have to set boundaries to make sure that the important things actually make it on your schedule, but it’s totally worth it to your overall level of happiness. I once told my advisor that I would not do certain types of academic activities because it would interfere with my work/life balance. He wasn’t happy at first, but later on accepted it and even said he admired me sticking to my guns on this (but, do pick your battles).
  • Don’t be afraid to ask for help — when you’re struggling or need something, ask for it. I hate asking for help, but I basically went crazy when I tried to handle everything myself. I’ve gotten help from my advisor, my committee members, my lab mates, my roommates, my extended academic family, my biological family, people I’ve met at CoC Happy Hour, and professionals (the Counseling Center at Georgia Tech is free for students, may be the same at your school). Don’t be afraid of looking lame. Sometimes you have to decide whether you want to save your face or your ass and the choice should be clear.

At the end of the post, he mentioned that

For me, I’m more productive when I’m happy. So, when I plan to “swim, do 8 hours of work, and have dinner with friends,” I actually get a lot more done than when I plan to “work for the next 16 hours.” And, I’m immeasurably happier.

This is really what I want!!!

Something is worth learning ahead of time: from the post

A real-time skill is something you need for live performance. If you’re going to speak French, you have to memorize a large number words before you need them in conversation. Looking up every word in a English-French dictionary as needed might work in the privacy of your study, but it would be infuriatingly slow in a face-to-face conversation. Some skills that we don’t think of as being real-time become real-time when you have to use them while interacting with other people.

More subtle than real-time skills are what I’m calling bicycle skills. Suppose you own a bicycle but haven’t learned to ride it. Each day you need to go to a store half a mile away. Each day you face the decision whether to walk or learn to ride the bicycle. It takes less time to just walk to the store than to learn to ride the bicycle and ride to the store. If you always do what is fastest that day, you’ll walk every day. I’m thinking of a bicycle skill as anything that doesn’t take too long to learn, quickly repays time invested, but will never happen without deliberate effort.

 

Today I just watched an interesting video about the indestructability of information and the nature of black holes, a talk given by Leonard Susskind of the Stanford Institute for Theoretical Physics.

Video: Leonard Susskind on The World As Hologram

And I also looked up some materials online:

World’s Most Precise Clocks Could Reveal Universe Is a Hologram

The World as a Hologram (A paper written by L. Susskind)

UC Berkeley’s Raphael Bousso presents a friendly introduction to the ideas behind the holographic principle, which may be very important in the hunt for a theory of quantum gravity.

1, The Origin of Kolmogorov Complexity

2, TED: Sheena Iyengar: How to make choosing easier – Sheena Iyengar (2011)

3, Remembering Steve Jobs

4, Graham Hill: Less stuff, more happiness

5, Simon Sinek: How great leaders inspire action

6, Improve Predictive Performance in R with Bagging

These days I have seen some discussion about simplicity.  Simplicity is relative and requires context. Something is simple to you but maybe not to others. More extremely,  the thing that human beings regard as simple may be very complicated to Martians. Why do human beings think something simple? This is a result of natural selection. People could only manage simple things. But simplicity does not imply no depth, neither goodness. Instead, simple is good. The simple thing we can sensor is the most deepest and important thing, which could be very hard and complicated thing for Martians. Our ability to capture the simple thing is really the natural selection by the nature. It’s kind of the result of reinforcement machine learning. The human beings have paid a lot to get the ability to capture the good and essential things, which are simple for us.

 For example, consider this mnemonic for pi:

How I want a drink, alcoholic of course, after the heavy lectures involving quantum mechanics.

This sentence is easier for most people to remember than 3.14159265358979.  But the sentence is also more complex. A computer can represent the number in 8 bytes but the sentence takes 94 bytes of ASCII, more in Unicode.

We need to reevaluate what we believe is simple. Maybe what we think is simple is complex but familiar. Maybe there is something new that is objectively simpler would become even easier once we’re used to it.

I gradually find that the following things are good for you to choose if you have many choices:

  1. R for Statistics
  2. Python for scientific computing
  3. Gimp for graphing
  4. Tex for typing
  5. WordPress  for blogging
  6. Gmail, google+, google sites, google reader,……
  7. Mendeley for managing your papers
  8. Delicious for discovering and collecting the web resources

All of them have a characteristic, i.e. Open Source or Free. And they all have big communities:

  1. R Revolution;  R bloggers
  2. Scipy.org
  3. Gimptalk
  4. Tex Users Group
And another thing is the following useful website I want to share:

After the whole summer struggling, I successfully passed the qualify exams. So I have to figure out what to work on in my PhD study. If you have any suggestions, please let me know.

1, What inspired you to work on… whatever you work on?

Grad students often wonder how people get ideas of things to work on. The usual advice I give is (1) go to talks, (2) read papers, (3) talk to people, (4) follow through on all of the above.

 

I am back from summer semester and I will write something and collect materials here again along the following fall semester.

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